Chattopadhyay, Mande and Sherif (to appear in STOC 2019) recently
exhibited a total Boolean function, the sink function, that has polynomial
approximate rank and polynomial randomized communication complexity. This gives
an exponential separation between randomized communication complexity and
logarithm of the approximate rank, refuting the log-approximate-rank conjecture.
We show that even the quantum communication complexity of the sink function is
polynomial, thus also refuting the quantum log-approximate-rank conjecture.
Our lower bound is based on the fooling distribution method introduced by Rao
and Sinha (Theory of Computing 2018) for the classical case and extended by
Anshu, Touchette, Yao and Yu (STOC 2017) for the quantum case. We also give a
new proof of the classical lower bound using the fooling distribution method.
Joint work with Ronald de Wolf.
exhibited a total Boolean function, the sink function, that has polynomial
approximate rank and polynomial randomized communication complexity. This gives
an exponential separation between randomized communication complexity and
logarithm of the approximate rank, refuting the log-approximate-rank conjecture.
We show that even the quantum communication complexity of the sink function is
polynomial, thus also refuting the quantum log-approximate-rank conjecture.
Our lower bound is based on the fooling distribution method introduced by Rao
and Sinha (Theory of Computing 2018) for the classical case and extended by
Anshu, Touchette, Yao and Yu (STOC 2017) for the quantum case. We also give a
new proof of the classical lower bound using the fooling distribution method.
Joint work with Ronald de Wolf.